Frontiers in Biomedical Technologies
Volume:10 Issue: 1, Winter 2023

There is significant interest and value in utilizing digital twins (DTs) to extend healthcare from ‘one-size-fits-all’ to personalized therapies. Radiopharmaceutical therapies (RPTs), which represent very powerful developments in the battle against cancer, are no exceptions to this. In fact, theranostic digital twins (TDTs), which we elaborate in this work, present viable and feasible approaches to personalize RPTs. TDTs are computational representations of the human body that, unlike images, are operable; i.e. virtual trials can be conducted on them to propose optimal therapies for individual patients. TDTs can be built using physiologically based pharmacokinetic (PBPK) models. This work elaborates that TDTs can be developed in static, dynamic and interactive modes towards routine use in future clinical settings. TDTs will open a new area of theranostics research and development in terms of new radiopharmaceutical designs, synthesis and enabling of more optimal therapies.

10% of the world's population suffers from chronic kidney disease and millions of deaths occur annually due to lack of access to appropriate treatment in the world. Kidney transplantation is associated with several problems. These problems, including kidney rejection, the consequences of surgery, drug poisoning, and infectious diseases can reduce the chances of survival of these patients. The science of classification has been proposed in recent years to reduce medical errors due to inexperience, reduce the workload of physicians and provide a suitable model for making better decisions.

The data set includes information about patients for whom kidney transplantation was performed in Isfahan. The data set includes 2554 patients and 38 attributes. The techniques used in this study will include random forest, Principal Component Analysis (PCA), and Support Vector Machine (SVM).

Among the studied techniques, PCA technique in three classes out of four classes had better performance than other techniques. The syndrome has the highest recurrence among traits. Five attributes include syndrome, blood type, dialysis time, weight, and age.

The results showed that the PCA method in the case of non-numerical data has a good performance in identifying attributes. Also, five attributes that affect the survival rate of kidney transplant patients were identified.

Gamma Knife Radiosurgery refers to surgery using radiation to destroy intracranial tissues or lesions elusive or unsuitable for open surgery. This study aimed to simulate the Gamma Knife Icon™ (GKI™) single sector to assess various attributes of the output beam and evaluate the EGSnrc C++ Monte Carlo code capabilities to perform a complete simulation of GKI™ for more investigations.

The single source is simulated, and the geometries of the 4 and 16 mm collimators are defined based on the manufacturer data. The phase space files (PSFs) are recorded at the end of each collimator, and dose distributions are saved for the final analysis process in the last step.

The beam spectrum has two energy peaks g1 =1.17 MeV and g2 = 1.33 MeV, and low energy photons from scattering are also evident. The Gamma Index (GI) values are less than 1 in comparing the dose profiles generated in simulation with reference data. The Full Width at Half Maximum (FWHM) is 4.55, 10.9, 5.13 (mm) and 16.7, 35.1, 17.65 (mm) for 4mm and 16 mm collimators along x, y, and z axes, respectively. The penumbra width (80%-20%) is also 1.48, 5.5, 1.54 (mm) and 3.76, 10.1, 2.78 (mm) for 4mm and 16 mm collimators along x, y, and z axes, respectively.

Results are in good agreement with what is expected, and it is possible to perform a complete simulation of the GKI™ system using egs++ for more investigations in phantoms and patients.

The production of the secondary neutron in the high-energy megavoltage medical accelerator machines has been extensively studied. In this study, MCNP5 MC code and two analytical methods, the proposed method and IAEA 47 proposed method were used to capture γ-ray dose equivalent calculation.

MCNP5 code of the MC simulation method was used for code calculation in this study. The main components of a Varian 2100Clinac were simulated as well as a 30×30×30 cm3 water phantom, in a Source to Surface Distance (SSD) of 100cm. Apparent neutron source strength (QN) was obtained using F1, *F8 tallies, and a small scoring cell at the isocenter with a mass equal to 0.625g.

.QN was obtained as 1.25 n/Gy X for the simulated linac head and was used in the other calculations. In the simulated double-bend maze treatment room with first and second lengths of the maze as 7m and 3m, the proposed method calculated capture γ-ray dose with 6.2% and 60% differences compared with MC simulation and IAEA 47 methods, respectively.

We concluded that Ghiasi and Mesbahi's proposed method performed better in capturing γ-ray dose equivalent calculation compared to IAEA 47 report. The proposed method reduced the difference from 60% to 6.2%.

Accurate knowledge about surface dose distribution is a critical issue in skin irradiation. This study was conducted to investigate the surface dose using the Eclipse Treatment Planning System (TPS) calculation and GAF chromic film measurement for breast cancer treatment.

An inhomogeneous chest phantom was used in the present study. Irradiations were done with a 6 MV energy beam of a linear accelerator (Varian 2100C/D). TPS calculations and film measurements were compared for surface dose estimations.

The average difference between film measurements and TPS calculations was 7.1%. Surface doses were lower in TPS calculations in comparison with film measurements.

TPS plays a significant role in radiotherapy. However, they have many errors in measuring surface doses. Because of the inaccuracy of the majority of treatment planning systems in calculating the surface dose, the need for practical measurements is essential.

Metal artifacts cause to increase in the uncorrected dose evaluation during radiotherapy planning. This study aimed to evaluate the probable difference of the dose parameters calculated by the Treatment Planning System (TPS) in radiotherapy of head and neck cancer before and after metal artifact correction in Neusoft-Philips Corporation Computed Tomography (CT) images.

In the present study, the radiotherapy planning of the head and neck cancer from thirty patients was first performed on the CT default images with dental implants. The same processes were applied after performing a body standard metal kernel on the CT images to reduce the metal artifacts. The Gross Tumor Volume (GTV) and Organ At Risks (OARs) were contoured on the CT slices. The dosimetric parameters (mean, minimum, and maximum) for the GTV and OARs (eyes and spinal cord) were obtained for both sets of CT images (defaults and filtered). Wilcoxon signed-rank test was used to calculate the probability dose variations between the two sets.

There are significant differences in several dose parameters between the default and filtered CT images (P-value < 0.05). These dosimetric parameters are related to the GTV (mean dose), spinal cord (minimum and mean doses), right eye (maximum dose), as well as left eye (mean dose). The average range of dose differences between the default and filtered images was obtained; 1.12%-3.11% for the GTV as well as 0.22%-12.05% for the OARs.

Based on the results, the body standard metal kernel can cause a significant difference in several dosimetric parameters of GTV and OARs during the radiotherapy of head and neck cancer. Therefore, it is recommended to make a metal artifact correction on CT images for accurate dose calculation before designing a treatment plan.

Measuring the blood flow velocity in capillaries is a useful method for diagnosing many diseases. Despite increasing interest in nailfold capillaroscopy, objective measures of capillary structure and blood flow have been rarely studied. This study aimed to measure the blood flow velocity along the capillary central line using capillaroscopy system, and also ImageJ software used Scale-Invariant Feature Transform (SIFT) tracking algorithms and Kalman filter for image processing.

The Red Blood Cells (RBCs) velocity in capillaries of finger nailfold was measured in 12 normal cases using a novel capillaroscopy system. The measurements of the velocity were performed at 12 points in nailfold regions by two observers separately. The image processing and automated measurement take 1-2 min per nailfold. FFmpeg software was used to convert the images format, and then the images were imported to ImageJ software and segmented. SIFT tracking algorithms and Kalman filter were used to filter noise and irregularities in the images. For reproducibility, the velocity distribution values obtained by the two performers, and Paired T-Test was used. The reliability of a measuring instrument or calculation method depends on the tools obtained using Cronbach's alpha. To assess the repeatability of the algorithm, the capillary velocity values were executed at different times with 24-hour intervals using a coefficient of variance method.

The calculated RBCs velocity was in the range of 0.05-0.16 mm/s. The results based on Cronbach's alpha analysis for reliability factor was 0.97, with a good correlation among the measurements, 0.85. The average velocity (along with standard deviation) for repeatability at three different times was obtained 0.1195 ± 0.0246, 0.0974 ± 0.0221, and 0.0962 ± 0.0202 mm/s, demonstrating that there was no statistically variation between these measurements (P-value > 0.05). The velocity results for the two observers were 0.811 ± 0.392 and 0.819 ± 0.325 mm/s, indicating a good reproducibility between them (P-value = 0.959).

For the measurements of nailfold capillaries velocity, there was good/reasonable reliability, repeatability, and reproducibility. The results indicated a good accuracy of capillaroscopy system and ImageJ software with SIFT algorithm and Kalman filter, which can be used as an appropriate tool for determining the rate of nailfold blood flow velocity.

Emotions are integral brain states that can influence our behavior, decision-making, and functions. Electroencephalogram (EEG) is an appropriate modality for emotion recognition since it has high temporal resolution and is a noninvasive and cheap technique.

A novel approach based on Ensemble pre-trained Convolutional Neural Networks (ECNNs) is proposed to recognize four emotional classes from EEG channels of individuals watching music video clips. First, scalograms are built from one-dimensional EEG signals by applying the Continuous Wavelet Transform (CWT) method. Then, these images are used to re-train five CNNs: AlexNet, VGG-19, Inception-v1, ResNet-18, and Inception-v3. Then, the majority voting method is applied to make the final decision about emotional classes. The 10-fold cross-validation method is used to evaluate the performance of the proposed method on EEG signals of 32 subjects from the DEAP database.

The experiments showed that applying the proposed ensemble approach in combinations of scalograms of frontal and parietal regions improved results. The best accuracy, sensitivity, precision, and F-score to recognize four emotional states achieved 96.90%±0.52, 97.30±0.55, 96.97±0.62, and 96.74±0.56, respectively.

So, the newly proposed model from EEG signals improves recognition of the four emotional states in the DEAP database.

The use of ionizing radiation in medical research, treatment, and diagnosis is inevitable and expanding day by day. Meanwhile, in two modes of Computed Tomography (CT) and Single Photon Emission Computed Tomography (SPECT) imaging, the dose received by the organs is featured with limitations and problems, which are often referred to as the CT Dose Index volume (CTDIvol.) and the Dose Length Product (DLP). This study aimed to estimate the average dose of organs and compare them in each of these two modalities.

Using the GATE code to simulate the SPECT-CT system and the ICRP voxelized phantom as the patient was investigated. The mean dose distribution in three groups of children, adults, and obese people with different body thicknesses was estimated. The dose received by each of the two systems was evaluated separately and results were discussed and analyzed comparatively.

In the kidney, bladder, intestine, colon, liver, and gallbladder, the dose received in CT is at least 10% more than nuclear medicine. For example, the ratio of the dose received in CT to the dose received in nuclear medicine in the lung was about 1.08 and in the esophagus was about 1.24. Subsequently, the ratio increased to 0.25 in the bladder and 0.19 in the colon and intestine. Moreover, the major organs that received the maximum dose, result in CT at least 10% more than nuclear medicine.

The dose received in organs such as the esophagus, breast, and lung during CT imaging protocol and also maximum dose were at least ten percent more than nuclear medicine.

Accurate measurement of Left Ventricular Ejection Fraction (LVEF (is essential for the diagnosis and prediction of LV arrhythmias. This study aims to estimate LVEF using nonlinear and statistical processing in echocardiography images. The Cardiac Acquisition for Multi-Structure Ultrasound Segmentation (CAMUS) dataset is used to estimate LVEF. This dataset includes ultrasound images data from 60 patients in two different group (LVEF>55%, LVEF<45%). Region growing technique and Anatomical markers were used for segmentation of LV in images to measure area changes. LV area changes have been investigated using nonlinear and statistical analysis. In order to facilitate the process of estimating LVEF, feature extraction and an ANN has been used. The results show that: (1) LV area changes in LVEF<45%, has a mean of (3.254) while LVEF>55% has a lower mean of (3.071) but the mean of variance is (3.818) while for LVEF<45% is (3.471) which can be concluded that the data scatter in LVEF>55% was higher than the mean and indicates larger changes in the LV region. Estimated LVEF using nonlinear and statistical features is shows MSE of (5.15).

Online determination of the elemental composition of tissues near the Bragg peak is a challenge in proton therapy related studies. In the present work, an analysis method based on the whole spectral information is presented for the quantitative determination of the elemental composition (weight %) of an irradiated target from its emitted Prompt Gamma (PG) spectrum.

To address this issue, four test phantoms with different weights (%) of 12C, 16O, 20Ca, and 14N elements were considered. The simulated PG spectra were recorded using 3 × 3 inch NaI detectors. A library consisting of the spectra of single-element phantoms as well as the spectra of test-irradiated phantoms was produced for 30, 70, and 150 MeV incident protons using the Geant4 Monte Carlo toolkit. The elemental analysis was performed using the information of the whole spectrum by applying two methods, including the well-known Genetic Algorithm (GA) and Multiple Linear Regression (MLR).

The results show that the proposed method estimates the oxygen concentration accurately. Furthermore, the estimated weights of other elements, with both methods, agree well with nominal values in each test phantom, for the considered energies.

The proposed quantitative elemental analysis of proton-bombarded phantoms using their induced PG spectrum is expected to be beneficial in treatment planning and treatment verification studies.

This study aimed to evaluate a lie-detection system by non-linear analysis of video-based eye movement.

The physiological signals, as well as video-based eye movement in horizontal and vertical channels, were recorded based on a Control Question Test (CQT). The dynamics of eye movement signals were then analyzed by Recurrence Quantification Analysis (RQA). Statistical analysis was performed by ANOVA and Linear Discriminate Analysis (LDA).

In this study, 40 subjects participated. The statistical analysis results of vertical eye movement indicated that ENT measures increased significantly for relevant questions in comparison to other questions. Moreover, a significant increase was observed in all RQA parameters except Lmax and DET for horizontal eye movement. The results of LDA using psychophysiology features. The accuracy percentage of 78.4% and 81.86% were obtained for lie detection using physiological signals and optimal RQA parameters of video-based eye movements, respectively.

The accuracy of lie detection by significant RQA parameters was more than the accuracy of physiological signals. So, the results of this study illustrate that the dynamic technique is well suited to analyze eye movement signals under stress and it could be recommended as a useful method in lie detection.

Radiation workers are exposed to chronic effects due to long-term exposure to low levels of ionizing radiation. One of the biological indicators to evaluate these chronic radiation effects is the study of the hematopoietic system. The purpose of this study is to compare the changes in blood parameters of radiology staff and staff of other wards of the hospital.

In this study, 47 radiology staff working in the radiology department of the hospital as the study group and 98 personnel in other departments as the control group were included. Demographic data including age, gender, and work experience were obtained. Hematological parameters were extracted from the complete blood count tests of participants.

The results of this study showed that the MCH and MCHC parameters significantly decreased in the male study group, whereas no significant differences were observed in the blood parameters of the female study group in comparison to those of the control group. There was a significant positive correlation between the parameters of Hemoglobin and age. There was a significant negative correlation between work experience and white blood cells, while there was a significant positive correlation between work experience and Hemoglobin.

Correlation between collective absorbed dose and changes in blood parameters is suggested for future studies. Based on the results of this study and other studies, it can be concluded that long-term exposure to low levels of radiation may change blood parameters. Therefore, regular and periodic complete blood count tests along with absorbed dose monitoring of radiation workers are recommended.

Calculating the organs' radiation dosage in cardiac nuclear medicine procedures is essential in order to identify critical organs, radiation risk assessment and optimization dose value in the injection of radiopharmaceutical drugs. In this study, the biological distribution of 99mTc-2-Methoxyisobutylisonitrile) 99mTc-MIBI as the most common radiopharmaceutical in a cardiac study in human organs based on animal samples was investigated.

After 99mTc-MIBI preparation, radiopharmaceutical was injected into 15 rats. After sacrificing rats, the uptake of radiopharmaceuticals in critical organs at 15, 30, and 45 minutes was measured using an High Purity Germanium (HPGE) detector and the percentage of injected dose per gram of organs was calculated. The cumulative activity was calculated from the radiopharmaceutical transformation diagram with time. The absorption of a radioactive complex in human organs based on animal data was calculated by applying a correction factor. The organs dose was calculated using S factor and the effective dose was calculated using tissue weighting factors.

The mean effective dose per unit of activity was 0.0062 mSv/MBq. The mean effective dose of 27.5 mCi radiopharmaceutical injection was 6.3 mSv. In this study, the absorbed dose in blood, heart, lung, thyroid, liver, spleen, stomach wall, muscle, and bone was calculated as 0.28, 2.92, 1.85, 24.82, 11.13, 7.03, 20.95, 1.11, 4.97, and 22.22 mGy, respectively.

The effective dose of human organs based on the animal model in the study of cardiac nuclear medicine was evaluated by injection of 99mTc-MIBI radiopharmaceutical. The kidneys, salivary glands, thyroid, and spleen were the most critical organs that should be considered in dose optimization studies. The effective dose limit was 28% lower than the values reported in international references.